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Likelihood Functions

Explore how to represent conditional probabilities as likelihood functions in C#. Understand the relationship between prior and likelihood distributions, and implement these concepts to compute marginal probabilities. This lesson demonstrates how to combine discrete distributions with practical examples of Cold and Sneezed states, enhancing your approach to probabilistic modeling in C#.

In the previous lesson, we implemented an efficient conditioned probability using the Where operator on distributions; that is, we have some “underlying” distribution, and we ask the question “if a particular condition has to be met, ...